A route map for successful applications of geographically weighted regression
Geographically Weighted Regression (GWR) is increasingly used in spatial analyses of
social and environmental data. It allows spatial heterogeneities in processes and …
social and environmental data. It allows spatial heterogeneities in processes and …
Impact of urbanization on ecosystem health in Chinese urban agglomerations
W Chen, G Wang, J Zeng - Environmental Impact Assessment Review, 2023 - Elsevier
With rapid economic growth, urbanization has interfered with regional ecosystems and
seriously threatens ecosystem health (EH) in urban agglomerations (UAs) in China …
seriously threatens ecosystem health (EH) in urban agglomerations (UAs) in China …
Geographically weighted regression
Spatial data contain locational information as well as attribute information. It is increasingly
recognized that most data sets are spatial in that the attribute being measured is typically …
recognized that most data sets are spatial in that the attribute being measured is typically …
Urbanization induced degradation of urban green space and its association to the land surface temperature in a medium-class city in India
T Basu, A Das - Sustainable Cities and Society, 2023 - Elsevier
A few recent studies revealed that the intensity of UHI is increasing in medium-class cities
due to the rapid degradation of natural vegetation covers. This study explores the patch …
due to the rapid degradation of natural vegetation covers. This study explores the patch …
Geographically weighted regression with a non-Euclidean distance metric: a case study using hedonic house price data
Geographically weighted regression (GWR) is an important local technique for exploring
spatial heterogeneity in data relationships. In fitting with Tobler's first law of geography, each …
spatial heterogeneity in data relationships. In fitting with Tobler's first law of geography, each …
How the built environment promotes public transportation in Wuhan: A multiscale geographically weighted regression analysis
R An, Z Wu, Z Tong, S Qin, Y Zhu, Y Liu - Travel Behaviour and Society, 2022 - Elsevier
During rapid urbanization, the optimization of the built environment in metropolises to
promote the use of public transportation considerably eases the road traffic pressure …
promote the use of public transportation considerably eases the road traffic pressure …
Geographically weighted regression
DC Wheeler - Handbook of regional science, 2021 - Springer
Geographically weighted regression (GWR) was proposed in the geography literature to
allow relationships in a regression model to vary over space. In contrast to traditional linear …
allow relationships in a regression model to vary over space. In contrast to traditional linear …
[HTML][HTML] A retrospective cross-national examination of COVID-19 outbreak in 175 countries: a multiscale geographically weighted regression analysis (January 11 …
Objective This study retrospectively examined the health and social determinants of the
COVID-19 outbreak in 175 countries from a spatial epidemiological approach. Methods We …
COVID-19 outbreak in 175 countries from a spatial epidemiological approach. Methods We …
Spatial heterogeneity in hedonic house price models: The case of Austria
Modelling spatial heterogeneity (SH) is a controversial subject in real estate economics.
Single-family-home prices in Austria are explored to investigate the capability of global and …
Single-family-home prices in Austria are explored to investigate the capability of global and …
Estimation and hypothesis testing for nonparametric hedonic house price functions
In contrast to the rigid structure of standard parametric hedonic analysis, nonparametric
estimators control for misspecified spatial effects while using highly flexible functional forms …
estimators control for misspecified spatial effects while using highly flexible functional forms …